Exploratory Data Analysis
Kevin Thompson, Sean Kennedy, Sachin Chavan
September 29, 2019
1 : Load required libraries
2 : Load Quarterback Crosssectional data
load("../analysis/data/.RData")
QBCrossSectional = getFootballData(URL) %>% filterUnwantedVariables() %>% filter(Position == 'QB')
summary(QBCrossSectional)## PlayerID Name Week Position
## Min. : 611 Length:453 Min. : 1.000 Length:453
## 1st Qu.: 7242 Class :character 1st Qu.: 5.000 Class :character
## Median :13723 Mode :character Median : 9.000 Mode :character
## Mean :11932 Mean : 9.049
## 3rd Qu.:16763 3rd Qu.:13.000
## Max. :19029 Max. :17.000
## Opponent TeamIsHome GameDate PassingCompletions
## Length:453 Mode :logical Length:453 Min. : 5.00
## Class :character FALSE:226 Class :character 1st Qu.:18.00
## Mode :character TRUE :227 Mode :character Median :21.00
## Mean :21.24
## 3rd Qu.:25.00
## Max. :44.00
## Result PassingAttempts PassingCompletionPercentage
## Length:453 Min. :10.00 Min. :38.70
## Class :character 1st Qu.:29.00 1st Qu.:57.10
## Mode :character Median :33.00 Median :63.20
## Mean :33.62 Mean :63.48
## 3rd Qu.:38.00 3rd Qu.:69.40
## Max. :66.00 Max. :87.00
## PassingYards PassingYardsPerAttempt PassingTouchdowns
## Min. : 57.0 Min. : 3.100 Min. :0.000
## 1st Qu.:199.0 1st Qu.: 6.200 1st Qu.:1.000
## Median :241.0 Median : 7.200 Median :1.000
## Mean :244.6 Mean : 7.378 Mean :1.587
## 3rd Qu.:291.0 3rd Qu.: 8.400 3rd Qu.:2.000
## Max. :506.0 Max. :14.100 Max. :5.000
## PassingInterceptions PassingRating RushingAttempts RushingYards
## Min. :0.00 Min. : 31.14 Min. : 0.000 Min. :-8.00
## 1st Qu.:0.00 1st Qu.: 77.92 1st Qu.: 1.000 1st Qu.: 0.00
## Median :0.00 Median : 92.94 Median : 3.000 Median : 8.00
## Mean :0.66 Mean : 93.88 Mean : 3.185 Mean :14.38
## 3rd Qu.:1.00 3rd Qu.:109.84 3rd Qu.: 5.000 3rd Qu.:23.00
## Max. :4.00 Max. :150.69 Max. :14.000 Max. :95.00
## RushingYardsPerAttempt RushingTouchdowns FumblesLost FantasyPoints
## Min. :-2.700 Min. :0.0000 Min. :0.0000 Min. : 7.12
## 1st Qu.: 0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:11.86
## Median : 3.000 Median :0.0000 Median :0.0000 Median :15.86
## Mean : 3.839 Mean :0.1457 Mean :0.1766 Mean :16.89
## 3rd Qu.: 6.000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:20.68
## Max. :70.000 Max. :2.0000 Max. :3.0000 Max. :37.64
## Team
## Length:453
## Class :character
## Mode :character
##
##
## attach(QBCrossSectional)## The following object is masked from package:ggplot2:
##
## PositionDrop rushing yards per attempt
3 : Defensive stats
## 3.1 : Team Defensive Statsteam_defense = getFootballData("https://fantasydata.com/FantasyStatsNFL/FantasyStats_Read?sort=FantasyPoints-desc&pageSize=4000&group=&filter=&filters.position=7&filters.team=&filters.teamkey=&filters.season=2017&filters.seasontype=1&filters.scope=2&filters.subscope=1&filters.redzonescope=&filters.scoringsystem=&filters.leaguetype=&filters.searchtext=&filters.week=&filters.startweek=1&filters.endweek=17&filters.minimumsnaps=&filters.teamaspect=&filters.stattype=&filters.exportType=&filters.desktop=&filters.dfsoperator=&filters.dfsslateid=&filters.dfsslategameid=&filters.dfsrosterslot=&filters.page=&filters.showfavs=&filters.posgroup=&filters.oddsstate=&filters.aggregatescope=1&filters.rangescope=&filters.range=1")
team_defense$StatSummary = c(NULL)
defensive_columns = c('Team', 'Week', 'TacklesForLoss', 'Sacks', 'QuarterbackHits', 'Interceptions', 'FumblesRecovered', 'Safeties', 'DefensiveTouchdowns', 'SoloTackles', 'AssistedTackles', 'SackYards', 'PassesDefended', 'FumblesForced', 'FantasyPoints', 'PointsAllowedByDefenseSpecialTeams')
team_defense = team_defense %>% dplyr::select(defensive_columns) %>% rename('DefensiveFantasyPoints'='FantasyPoints')
attach(team_defense)## The following objects are masked from QBCrossSectional:
##
## Team, Week## 3.5 : Add defensive matchups#This only adds the current weeks matchup - we need next week's matchup as a target
team_defense_custom = sqldf("SELECT Team
,Week
,(Sacks * 4
+QuarterbackHits * 3
+Interceptions * 7
+SackYards * 2) as PassingDefense
,PointsAllowedByDefenseSpecialTeams
FROM team_defense")
#scheme: weight interceptions, qbsacks, quarterbackhits, passesdefended
plot(team_defense_custom$PassingDefense, team_defense_custom$PointsAllowedByDefenseSpecialTeams)
team_defensive_rankings = team_defense_custom %>%
#filter(Week > 1 & Week < 17)
group_by(Team) %>%
arrange(Week) %>%
mutate(
AvgPassDefense = cumsum(PassingDefense)/Week #Account for bye week....
)
QBCrossSectional$Week = as.numeric(QBCrossSectional$Week)
hist(team_defensive_rankings$AvgPassDefense)
sqldf("SELECT * FROM team_defensive_rankings WHERE Team = 'LAC'")## Team Week PassingDefense PointsAllowedByDefenseSpecialTeams
## 1 LAC 1 126 24
## 2 LAC 2 27 19
## 3 LAC 3 101 24
## 4 LAC 4 29 26
## 5 LAC 5 132 20
## 6 LAC 6 33 16
## 7 LAC 7 95 0
## 8 LAC 8 59 19
## 9 LAC 10 76 20
## 10 LAC 11 62 24
## 11 LAC 12 56 6
## 12 LAC 13 63 10
## 13 LAC 14 60 7
## 14 LAC 15 26 30
## 15 LAC 16 76 7
## 16 LAC 17 54 10
## AvgPassDefense
## 1 126.00000
## 2 76.50000
## 3 84.66667
## 4 70.75000
## 5 83.00000
## 6 74.66667
## 7 77.57143
## 8 75.25000
## 9 67.80000
## 10 67.27273
## 11 66.33333
## 12 66.07692
## 13 65.64286
## 14 63.00000
## 15 63.81250
## 16 63.23529## 3.6 : Add some lag data for QB
### CumulativeVariables (these should definitley be combined into a weekly ranking)QBCrossSectionalCumulativePassYards = QBCrossSectional %>% group_by(PlayerID)%>% filter(n() >= 8) %>% arrange(Week) %>%
mutate(CumulativeAveragePassingYards=cummean(PassingYards)
, CumulativeAveragePassingTouchdowns=cummean(PassingTouchdowns)
, CumulativeAveragePassingInterceptions=cummean(PassingInterceptions)
, CumulativeAveragePassingRating=cummean(PassingRating)
, CumulativeAverageCompletions = cummean(PassingCompletions) # not sure that completions matter much - most leagues don't reward them
, CumulativeAverageCompletionPercentage = cummean(PassingCompletionPercentage)
, CumulativeMaxPassingTouchdowns = cummax(PassingTouchdowns)
, CumulativeMaxPassingYards = cummax(PassingYards)
, CumulativeMaxPassingAttempts = cummax(PassingAttempts)
, CumulativeMaxPassingRating = cummax(PassingRating)
, CumulativeMaxCompletions = cummax(PassingCompletions)
, CumulativeMaxPassYardsPerAttempt = cummax(PassingYardsPerAttempt)
, CumulativeMinPassingTouchdowns = cummin(PassingTouchdowns)
, CumulativeMinPassingYards = cummin(PassingYards) #Let's get mins to capture downside risk
, CumulativeMinPassingAttempts = cummin(PassingAttempts)
, CumulativeMinPassingRating = cummin(PassingRating)
, CumulativeMinCompletions = cummin(PassingCompletions)
, CumulativeMinPassYardsPerAttempt = cummin(PassingYardsPerAttempt)
, NextWeekFantasyPoints = lead(FantasyPoints) #Target Variable
, NextOpponent = lead(Opponent)
#, NextWeekDefensiveMatchup = lag(WeeklyRank) #Has to be last week's team ranking - not this week
)
QBCrossSectionalDefensiveOverlayCumulativePassYards = QBCrossSectionalCumulativePassYards %>% left_join(team_defensive_rankings, by = c('Week'='Week', 'NextOpponent'='Team'))
#QBCrossSectionalDefensiveOverlayCumulativePassYards %>% filter(PlayerID == 6739) %>% write.csv('alex_smith.csv') #Alex Smith did indeed pass for 4042 yards on the season:)
attach(QBCrossSectionalDefensiveOverlayCumulativePassYards)## The following objects are masked from team_defense:
##
## PointsAllowedByDefenseSpecialTeams, Team, Week## The following objects are masked from QBCrossSectional:
##
## FantasyPoints, FumblesLost, GameDate, Name, Opponent,
## PassingAttempts, PassingCompletionPercentage,
## PassingCompletions, PassingInterceptions, PassingRating,
## PassingTouchdowns, PassingYards, PassingYardsPerAttempt,
## PlayerID, Position, Result, RushingAttempts,
## RushingTouchdowns, RushingYards, RushingYardsPerAttempt, Team,
## TeamIsHome, Week## The following object is masked from package:ggplot2:
##
## Positionsummary(QBCrossSectionalDefensiveOverlayCumulativePassYards)## PlayerID Name Week Position
## Min. : 611 Length:368 Min. : 1.000 Length:368
## 1st Qu.: 6739 Class :character 1st Qu.: 4.000 Class :character
## Median :13320 Mode :character Median : 9.000 Mode :character
## Mean :11765 Mean : 8.924
## 3rd Qu.:16763 3rd Qu.:13.000
## Max. :18868 Max. :17.000
##
## Opponent TeamIsHome GameDate PassingCompletions
## Length:368 Mode :logical Length:368 Min. : 6.00
## Class :character FALSE:184 Class :character 1st Qu.:18.00
## Mode :character TRUE :184 Mode :character Median :21.00
## Mean :21.39
## 3rd Qu.:25.00
## Max. :44.00
##
## Result PassingAttempts PassingCompletionPercentage
## Length:368 Min. :10.00 Min. :39.30
## Class :character 1st Qu.:29.00 1st Qu.:57.40
## Mode :character Median :33.00 Median :63.75
## Mean :33.56 Mean :63.99
## 3rd Qu.:38.00 3rd Qu.:70.00
## Max. :66.00 Max. :87.00
##
## PassingYards PassingYardsPerAttempt PassingTouchdowns
## Min. : 69.0 Min. : 3.100 Min. :0.000
## 1st Qu.:202.8 1st Qu.: 6.300 1st Qu.:1.000
## Median :242.0 Median : 7.300 Median :1.500
## Mean :246.8 Mean : 7.442 Mean :1.617
## 3rd Qu.:292.2 3rd Qu.: 8.400 3rd Qu.:2.000
## Max. :506.0 Max. :14.100 Max. :5.000
##
## PassingInterceptions PassingRating RushingAttempts RushingYards
## Min. :0.0000 Min. : 31.14 Min. : 0.000 Min. :-8.00
## 1st Qu.:0.0000 1st Qu.: 79.29 1st Qu.: 1.000 1st Qu.: 0.00
## Median :0.0000 Median : 94.94 Median : 3.000 Median : 8.00
## Mean :0.6114 Mean : 95.45 Mean : 3.258 Mean :14.55
## 3rd Qu.:1.0000 3rd Qu.:110.83 3rd Qu.: 5.000 3rd Qu.:24.00
## Max. :4.0000 Max. :150.69 Max. :14.000 Max. :95.00
##
## RushingYardsPerAttempt RushingTouchdowns FumblesLost FantasyPoints
## Min. :-2.700 Min. :0.0000 Min. :0.0000 Min. : 7.32
## 1st Qu.: 0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:12.61
## Median : 3.000 Median :0.0000 Median :0.0000 Median :16.16
## Mean : 3.818 Mean :0.1495 Mean :0.1793 Mean :17.22
## 3rd Qu.: 6.050 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:20.70
## Max. :70.000 Max. :2.0000 Max. :3.0000 Max. :37.64
##
## Team CumulativeAveragePassingYards
## Length:368 Min. :120.5
## Class :character 1st Qu.:221.9
## Mode :character Median :247.8
## Mean :246.6
## 3rd Qu.:271.5
## Max. :369.0
##
## CumulativeAveragePassingTouchdowns CumulativeAveragePassingInterceptions
## Min. :0.000 Min. :0.0000
## 1st Qu.:1.250 1st Qu.:0.4125
## Median :1.667 Median :0.5714
## Mean :1.584 Mean :0.5933
## 3rd Qu.:2.000 3rd Qu.:0.7500
## Max. :4.000 Max. :2.0000
##
## CumulativeAveragePassingRating CumulativeAverageCompletions
## Min. : 56.25 Min. :10.00
## 1st Qu.: 87.77 1st Qu.:19.56
## Median : 97.01 Median :21.85
## Mean : 95.86 Mean :21.43
## 3rd Qu.:102.53 3rd Qu.:23.13
## Max. :148.57 Max. :29.00
##
## CumulativeAverageCompletionPercentage CumulativeMaxPassingTouchdowns
## Min. :44.40 Min. :0.00
## 1st Qu.:61.60 1st Qu.:2.00
## Median :64.13 Median :3.00
## Mean :64.42 Mean :2.91
## 3rd Qu.:67.37 3rd Qu.:4.00
## Max. :80.00 Max. :5.00
##
## CumulativeMaxPassingYards CumulativeMaxPassingAttempts
## Min. :125.0 Min. :21.00
## 1st Qu.:288.0 1st Qu.:39.00
## Median :332.0 Median :44.00
## Mean :331.3 Mean :43.31
## 3rd Qu.:368.0 3rd Qu.:49.00
## Max. :506.0 Max. :66.00
##
## CumulativeMaxPassingRating CumulativeMaxCompletions
## Min. : 56.25 Min. :11.00
## 1st Qu.:110.80 1st Qu.:25.00
## Median :125.96 Median :28.00
## Mean :123.69 Mean :27.42
## 3rd Qu.:141.79 3rd Qu.:30.00
## Max. :150.69 Max. :44.00
##
## CumulativeMaxPassYardsPerAttempt CumulativeMinPassingTouchdowns
## Min. : 4.800 Min. :0.0000
## 1st Qu.: 8.500 1st Qu.:0.0000
## Median :10.500 Median :0.0000
## Mean : 9.859 Mean :0.4647
## 3rd Qu.:10.900 3rd Qu.:1.0000
## Max. :14.100 Max. :4.0000
##
## CumulativeMinPassingYards CumulativeMinPassingAttempts
## Min. : 69.0 Min. :10.00
## 1st Qu.:128.0 1st Qu.:21.00
## Median :158.0 Median :24.00
## Mean :168.1 Mean :24.13
## 3rd Qu.:204.0 3rd Qu.:27.00
## Max. :369.0 Max. :41.00
##
## CumulativeMinPassingRating CumulativeMinCompletions
## Min. : 31.14 Min. : 6.00
## 1st Qu.: 59.66 1st Qu.:12.00
## Median : 68.58 Median :14.00
## Mean : 69.27 Mean :14.91
## 3rd Qu.: 77.92 3rd Qu.:17.00
## Max. :148.57 Max. :29.00
##
## CumulativeMinPassYardsPerAttempt NextWeekFantasyPoints NextOpponent
## Min. : 3.100 Min. : 7.32 Length:368
## 1st Qu.: 4.800 1st Qu.:12.79 Class :character
## Median : 5.800 Median :16.23 Mode :character
## Mean : 5.704 Mean :17.33
## 3rd Qu.: 6.200 3rd Qu.:20.91
## Max. :11.200 Max. :37.64
## NA's :28
## PassingDefense PointsAllowedByDefenseSpecialTeams AvgPassDefense
## Min. : 0.00 Min. : 0.00 Min. : 13.00
## 1st Qu.: 30.00 1st Qu.:16.00 1st Qu.: 46.22
## Median : 54.00 Median :21.00 Median : 60.17
## Mean : 56.76 Mean :21.48 Mean : 59.85
## 3rd Qu.: 76.00 3rd Qu.:27.00 3rd Qu.: 69.40
## Max. :200.00 Max. :51.00 Max. :200.00
## NA's :51 NA's :51 NA's :51 ## 3.7 : Create indepenent structure for EDA from QBCrossSectional Dataeda_base <- QBCrossSectional %>% group_by(Week) %>%
select(Week,
FantasyPoints,
PassingCompletions,
PassingAttempts,
PassingCompletionPercentage,
PassingYards,
PassingYardsPerAttempt,
PassingTouchdowns,
PassingInterceptions,
PassingRating,
RushingAttempts,
RushingYards,
RushingYardsPerAttempt,
RushingTouchdowns,
FumblesLost
)
eda_base$Week <- as.factor(eda_base$Week) ## 3.8 : Create indepenent structure for derived features for EDA
from QBCrossSectionalDefensiveOverlayCumulativePassYards Dataeda_derived <- QBCrossSectionalDefensiveOverlayCumulativePassYards %>% group_by(Week)%>%
select(Week,
FantasyPoints,
CumulativeAveragePassingYards,
CumulativeAveragePassingTouchdowns,
CumulativeAveragePassingInterceptions,
CumulativeAveragePassingRating,
CumulativeAverageCompletions,
CumulativeAverageCompletionPercentage,
CumulativeMaxPassingTouchdowns,
CumulativeMaxPassingYards,
CumulativeMaxPassingAttempts,
CumulativeMaxPassingRating,
CumulativeMaxCompletions,
CumulativeMaxPassYardsPerAttempt,
CumulativeMinPassingTouchdowns,
CumulativeMinPassingYards,
CumulativeMinPassingAttempts,
CumulativeMinPassingRating,
CumulativeMinCompletions,
CumulativeMinPassYardsPerAttempt)
eda_derived$Week <- as.factor(eda_derived$Week)4 : Structures QBCrossSectional (Quarterbacks)
summary(QBCrossSectional)## PlayerID Name Week Position
## Min. : 611 Length:453 Min. : 1.000 Length:453
## 1st Qu.: 7242 Class :character 1st Qu.: 5.000 Class :character
## Median :13723 Mode :character Median : 9.000 Mode :character
## Mean :11932 Mean : 9.049
## 3rd Qu.:16763 3rd Qu.:13.000
## Max. :19029 Max. :17.000
## Opponent TeamIsHome GameDate PassingCompletions
## Length:453 Mode :logical Length:453 Min. : 5.00
## Class :character FALSE:226 Class :character 1st Qu.:18.00
## Mode :character TRUE :227 Mode :character Median :21.00
## Mean :21.24
## 3rd Qu.:25.00
## Max. :44.00
## Result PassingAttempts PassingCompletionPercentage
## Length:453 Min. :10.00 Min. :38.70
## Class :character 1st Qu.:29.00 1st Qu.:57.10
## Mode :character Median :33.00 Median :63.20
## Mean :33.62 Mean :63.48
## 3rd Qu.:38.00 3rd Qu.:69.40
## Max. :66.00 Max. :87.00
## PassingYards PassingYardsPerAttempt PassingTouchdowns
## Min. : 57.0 Min. : 3.100 Min. :0.000
## 1st Qu.:199.0 1st Qu.: 6.200 1st Qu.:1.000
## Median :241.0 Median : 7.200 Median :1.000
## Mean :244.6 Mean : 7.378 Mean :1.587
## 3rd Qu.:291.0 3rd Qu.: 8.400 3rd Qu.:2.000
## Max. :506.0 Max. :14.100 Max. :5.000
## PassingInterceptions PassingRating RushingAttempts RushingYards
## Min. :0.00 Min. : 31.14 Min. : 0.000 Min. :-8.00
## 1st Qu.:0.00 1st Qu.: 77.92 1st Qu.: 1.000 1st Qu.: 0.00
## Median :0.00 Median : 92.94 Median : 3.000 Median : 8.00
## Mean :0.66 Mean : 93.88 Mean : 3.185 Mean :14.38
## 3rd Qu.:1.00 3rd Qu.:109.84 3rd Qu.: 5.000 3rd Qu.:23.00
## Max. :4.00 Max. :150.69 Max. :14.000 Max. :95.00
## RushingYardsPerAttempt RushingTouchdowns FumblesLost FantasyPoints
## Min. :-2.700 Min. :0.0000 Min. :0.0000 Min. : 7.12
## 1st Qu.: 0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:11.86
## Median : 3.000 Median :0.0000 Median :0.0000 Median :15.86
## Mean : 3.839 Mean :0.1457 Mean :0.1766 Mean :16.89
## 3rd Qu.: 6.000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:20.68
## Max. :70.000 Max. :2.0000 Max. :3.0000 Max. :37.64
## Team
## Length:453
## Class :character
## Mode :character
##
##
## 5 : struture with Derived features
summary(eda_derived)## Week FantasyPoints CumulativeAveragePassingYards
## 2 : 25 Min. : 7.32 Min. :120.5
## 3 : 24 1st Qu.:12.61 1st Qu.:221.9
## 4 : 24 Median :16.16 Median :247.8
## 13 : 24 Mean :17.22 Mean :246.6
## 14 : 24 3rd Qu.:20.70 3rd Qu.:271.5
## 7 : 23 Max. :37.64 Max. :369.0
## (Other):224
## CumulativeAveragePassingTouchdowns CumulativeAveragePassingInterceptions
## Min. :0.000 Min. :0.0000
## 1st Qu.:1.250 1st Qu.:0.4125
## Median :1.667 Median :0.5714
## Mean :1.584 Mean :0.5933
## 3rd Qu.:2.000 3rd Qu.:0.7500
## Max. :4.000 Max. :2.0000
##
## CumulativeAveragePassingRating CumulativeAverageCompletions
## Min. : 56.25 Min. :10.00
## 1st Qu.: 87.77 1st Qu.:19.56
## Median : 97.01 Median :21.85
## Mean : 95.86 Mean :21.43
## 3rd Qu.:102.53 3rd Qu.:23.13
## Max. :148.57 Max. :29.00
##
## CumulativeAverageCompletionPercentage CumulativeMaxPassingTouchdowns
## Min. :44.40 Min. :0.00
## 1st Qu.:61.60 1st Qu.:2.00
## Median :64.13 Median :3.00
## Mean :64.42 Mean :2.91
## 3rd Qu.:67.37 3rd Qu.:4.00
## Max. :80.00 Max. :5.00
##
## CumulativeMaxPassingYards CumulativeMaxPassingAttempts
## Min. :125.0 Min. :21.00
## 1st Qu.:288.0 1st Qu.:39.00
## Median :332.0 Median :44.00
## Mean :331.3 Mean :43.31
## 3rd Qu.:368.0 3rd Qu.:49.00
## Max. :506.0 Max. :66.00
##
## CumulativeMaxPassingRating CumulativeMaxCompletions
## Min. : 56.25 Min. :11.00
## 1st Qu.:110.80 1st Qu.:25.00
## Median :125.96 Median :28.00
## Mean :123.69 Mean :27.42
## 3rd Qu.:141.79 3rd Qu.:30.00
## Max. :150.69 Max. :44.00
##
## CumulativeMaxPassYardsPerAttempt CumulativeMinPassingTouchdowns
## Min. : 4.800 Min. :0.0000
## 1st Qu.: 8.500 1st Qu.:0.0000
## Median :10.500 Median :0.0000
## Mean : 9.859 Mean :0.4647
## 3rd Qu.:10.900 3rd Qu.:1.0000
## Max. :14.100 Max. :4.0000
##
## CumulativeMinPassingYards CumulativeMinPassingAttempts
## Min. : 69.0 Min. :10.00
## 1st Qu.:128.0 1st Qu.:21.00
## Median :158.0 Median :24.00
## Mean :168.1 Mean :24.13
## 3rd Qu.:204.0 3rd Qu.:27.00
## Max. :369.0 Max. :41.00
##
## CumulativeMinPassingRating CumulativeMinCompletions
## Min. : 31.14 Min. : 6.00
## 1st Qu.: 59.66 1st Qu.:12.00
## Median : 68.58 Median :14.00
## Mean : 69.27 Mean :14.91
## 3rd Qu.: 77.92 3rd Qu.:17.00
## Max. :148.57 Max. :29.00
##
## CumulativeMinPassYardsPerAttempt
## Min. : 3.100
## 1st Qu.: 4.800
## Median : 5.800
## Mean : 5.704
## 3rd Qu.: 6.200
## Max. :11.200
## 6 : QBCrossSectional - Check Missing Data
vis_dat(QBCrossSectional)
7 : Corrrelogram
## 7.1 : Base Feature Set
corr <- round(cor(eda_base[-1]), 1)
ggcorrplot(corr, hc.order = TRUE,
type = "full",
lab = TRUE,
lab_size = 1.5,
method="square",
colors = c("tomato2", "white", "springgreen3"),
title ="Correlogram of Base QB features",
tl.cex = 7,pch=2,pch.col =3,show.diag = T,
ggtheme=theme_classic)
## 7.2 : Derived Feature Setcorr <- round(cor(eda_derived[-1]), 1)
ggcorrplot(corr, hc.order = TRUE,
type = "full",
lab = TRUE,
lab_size = 1.5,
method="square",
colors = c("tomato2", "white", "springgreen3"),
title = "Correlogram of Derived QB features",
tl.cex = 7,pch=2,pch.col =3,show.diag = T,
ggtheme=theme_classic)
8 : Distributions
## 8.1 Density plot for Fantasypoints is approxmiately Normalpar(mfrow=c(1, 2)) # divide graph area in 2 columns
target <- QBCrossSectional$FantasyPoints
plot(density(target), main="CrossSectional Dataset: FantasyPoints", ylab="Frequency", sub=paste("Skewness:", round(e1071::skewness(target), 2)))
polygon(density(target), col="red")
# 8.2 : Boxplots - Target and Individual Predictor Bevavior for per Team
## 8.2.1 Base Feature seteda_base %>% ggplot(aes(y=FantasyPoints,x=Week,fill=Week,group=Week))+
geom_boxplot(show.legend = FALSE)+
xlab("Week")+ylab("FantasyPoints")+
labs(title="Fantasyfootball",
subtitle="Weekly fantasypoints",
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5))) 
for (i in 2:15) {
ggplotp <- eda_base %>%
ggplot(aes_string(y=names(eda_base[i]),x="Week",fill="Week",group="Week"))+
geom_boxplot(show.legend = FALSE)+
xlab("Week")+ylab(names(eda_base[i]))+
labs(title="Fantasyfootball",
subtitle=names(eda_base[i]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(ggplotp)
}
## 8.2.3 Boxplots Derived Feature seteda_derived %>% ggplot(aes(y=FantasyPoints,x=Week,fill=Week,group=Week))+
geom_boxplot(show.legend = FALSE)+
xlab("Week")+ylab("FantasyPoints")+
labs(title="Fantasyfootball",
subtitle="Weekly fantasypoints",
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5))) 
for (i in 2:20) {
ggplotp <- eda_derived %>%
ggplot(aes_string(y=names(eda_derived[i]),x="Week",fill="Week",group="Week"))+
geom_boxplot(show.legend = FALSE)+
xlab("Week")+ylab(names(eda_derived[i]))+
labs(title="Fantasyfootball",
subtitle=names(eda_derived[i]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(ggplotp)
}
## 8.3 Violin plots Derived Feature seteda_derived %>% ggplot(aes(y=FantasyPoints,x=Week,fill=Week,group=Week))+
geom_violin(show.legend = FALSE)+
xlab("Week")+ylab("FantasyPoints")+
labs(title="Fantasyfootball",
subtitle="Weekly fantasypoints",
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5))) 
for (i in 2:20) {
ggplotp <- eda_derived %>%
ggplot(aes_string(y=names(eda_derived[i]),x="Week",fill="Week",group="Week"))+
geom_violin(show.legend = FALSE)+
xlab("Week")+ylab(names(eda_derived[i]))+
labs(title="Fantasyfootball",
subtitle=names(eda_derived[i]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(ggplotp)
}
### Check for skewed predictors
## 8.4 : Histograms - Normality by Week
### 8.4.1 : Base feature Setfeatures_to_keep = c('PassingYards', 'PassingAttempts', 'PassingTouchdowns', 'PassingCompletions', 'PassingYardsPerAttempt')
for(f in features_to_keep){
hist = eda_base %>% ggplot(aes_string(x=f,fill="Week"))+
geom_histogram(bins=30,show.legend = FALSE)+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(hist)
}
### 8.4.2 : Dervived feature Setfeatures_to_keep = names(eda_derived[-1])
for(f in features_to_keep){
hist = eda_derived %>% ggplot(aes_string(x=f,fill="Week"))+
geom_histogram(bins=30,show.legend = FALSE)+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(hist)
}
## 8.5 Bar plots Derived Feature setfor(p in 2:20){
bar_plot <- eda_derived %>%
ggplot(aes_string(x="Week",
y=names(eda_derived[p]),
fill="Week",group="Week"))+
ggtitle(names(eda_derived[p]))+
geom_bar(stat="identity", width=.5, show.legend = FALSE)+
xlab("Week")+
ylab(names(eda_derived[p]))+
labs(title="Fantasyfootball",
subtitle=names(eda_derived[p]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(bar_plot)
}
9 : Scatterplots
We are trying to capture what the NEXT value for fantasy points is likely to be - these are all going to be highly correlated to the
current week since the fantasy score is a linear combination of the predictors for any given week.
We need to shift the data before running these charts.
## 9.1 : Scatterplots for base featuresfor (i in 2:15) {
base_scatter <- eda_base %>%
ggplot(aes_string(y="FantasyPoints",x=names(eda_base[i]),color="as.numeric(Week)")) +
geom_point()+geom_smooth(method="lm",se=F)+
labs(title="Fantasyfootball",
subtitle=names(eda_base[i]),
aption="Source: Fantasyfootball")+
labs(color="Week")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5))
)
print(base_scatter)
}
## 9.2 : Scatterplots for Derived featuresfor (i in 2:20) {
derived_scatter <- eda_derived %>%
ggplot(aes_string(y="FantasyPoints",x=names(eda_derived[i]),color="as.numeric(Week)"))+
geom_point()+
geom_smooth(method="lm",se=F)+
xlab(names(eda_derived[i]))+
ylab("FantasyPoints")+
labs(title="Fantasyfootball",
subtitle=names(eda_derived[i]),
aption="Source: Fantasyfootball")+
labs(color="Week")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5))
)
print(derived_scatter)
}
10 : Line plots
## 10.1 Base Features
line_ds <- eda_base %>% group_by(Week) %>% arrange(Week)
for(p in 2:15){
line_plot <- line_ds %>%
ggplot(aes_string(x="as.numeric(Week)",y=names(line_ds[p])))+
ggtitle(names(line_ds[p]))+
geom_line(show.legend = FALSE)+
xlab("Week")+
ylab(names(line_ds[p]))+
labs(title="Fantasyfootball",
subtitle=names(line_ds[p]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(line_plot)
}
## 10.2 Derived Features
line_ds <- eda_derived %>% group_by(Week) %>% arrange(Week)
for(p in 2:20){
line_plot <- line_ds %>%
ggplot(aes_string(x="as.numeric(Week)",y=names(line_ds[p])))+
ggtitle(names(line_ds[p]))+
geom_line(show.legend = FALSE)+
xlab("Week")+
ylab(names(line_ds[p]))+
labs(title="Fantasyfootball",
subtitle=names(line_ds[p]),
aption="Source: Fantasyfootball")+
theme_wsj()+
theme(plot.title = element_text(size = rel(0.5)),
plot.subtitle = element_text(size = rel(0.5)),
axis.text.x = element_text(angle=65, vjust=0.6,size=1),
axis.title = element_text(size = rel(0.5)),
legend.position = "right",
legend.direction ="vertical",
legend.title = element_text(size = rel(0.5)))
print(line_plot)
}
